From d758097c9b58a01f77cc65746558166b12602e07 Mon Sep 17 00:00:00 2001
From: cpetinon <168358472+cpetinon@users.noreply.github.com>
Date: Mon, 10 Jun 2024 15:03:10 +0200
Subject: [PATCH] Update preprocessing.R

---
 R/preprocessing.R | 75 ++++++++++++++++++++++++-----------------------
 1 file changed, 39 insertions(+), 36 deletions(-)

diff --git a/R/preprocessing.R b/R/preprocessing.R
index d95f3b3..29a44d0 100644
--- a/R/preprocessing.R
+++ b/R/preprocessing.R
@@ -1,12 +1,15 @@
+#' @description
+#' A short description...
 #' Retrieve hours with no data and replace incomplete data with NA,
 #'
+#'
 #' @param enriched_data enriched data.frame containing all the data for all your sensors
 #' @param date_range Date vector. example: c('2021-01-01','2022-01-01'). Full period if NULL (default).
 #' @param segments Character vector. Selected road segment, all if NULL (default).
 #' @param successive_day Integer. Number of day choosen. Default to 2
 #' @param uptime_choice Real. Uptime choosen. Default to 0.5
-#'
-#' @return enriched_data
+#' 
+#' @return enriched_data 
 #' @export
 #'
 #' @import dplyr
@@ -19,46 +22,50 @@
 #'                       segment = 'RteVitre-06',
 #'                       uptime_choice=0.3,
 #'                       successive_day=1)
+
 retrieve_missing_data<- function(enriched_data,
                                  date_range = NULL,
                                  segments = NULL,
                                  uptime_choice=0.5,
                                  successive_day=2)
 {
-
+  
   if(!is.null(segments))
   {enriched_data<-enriched_data[enriched_data$segment_name==segments,]}
-
+  
   if(!is.null(date_range))
   {enriched_data<-enriched_data[enriched_data$day>=date_range[1] & enriched_data$day<= date_range[2],]}
-
+  
   if(length(enriched_data$car)==0){stop("No data in the selectionned period")}
-
+  
   else
   {
     #Hours with no data
-    enriched_data<-retrieve_missing_hours(enriched_data,uptime_choice)
-
+    enriched_data<-retrieve_missing_hours(enriched_data,uptime_choice) 
+    
     #Inactivity Period
     enriched_data <- enriched_data %>%
       mutate(
-        heavy_NA = .data$heavy,
-        car_NA = .data$car,
-        bike_NA = .data$bike,
-        pedestrian_NA = .data$pedestrian
-      )
+        heavy_NA = heavy,
+        car_NA = car,
+        bike_NA = bike,
+        pedestrian_NA = pedestrian
+      )   
 
     replace_inactivity_period(enriched_data,successive_day,uptime_choice)
   }
     return(enriched_data)
 }
 
-#' Retrieve hours with no data
+#' @description
+#' A short description...
+#' Retrieve hours with no data 
+#'
 #'
 #' @param enriched_data enriched data.frame containing all the data for all your sensors
 #' @param uptime_choice Real. Uptime choosen. Default to 0.5
-#'
-#' @return enriched_data
+#' 
+#' @return enriched_data 
 #' @export
 #'
 #' @import dplyr
@@ -68,35 +75,31 @@ retrieve_missing_data<- function(enriched_data,
 #' retrieve_missing_hours(traffic)
 #' retrieve_missing_hours(traffic,
 #'                         uptime_choice=0.3)
+                       
 retrieve_missing_hours<-function(enriched_data,uptime_choice)
 {
-  enriched_data$date <- ymd_hms(enriched_data$date)
+  enriched_data$date <- ymd_hms(enriched_data$date) 
   enriched_data$season <- ifelse(month(enriched_data$date) %in% c(3,4,5), "Spring",
                                ifelse(month(enriched_data$date) %in% c(6,7,8), "Summer",
                                       ifelse(month(enriched_data$date) %in% c(9,10,11), "Autumn", "Winter")))
 
-  df_season<-enriched_data %>%
-    group_by(.data$segment_id,
-             .data$season,
-             .data$hour) %>%
-    summarise(condition=any(.data$car!=0 & .data$uptime>uptime_choice))
+  df_season<-enriched_data %>% group_by(segment_id,season,hour) %>% summarise(condition=any(car!=0 & uptime>uptime_choice))
 
-  enriched_data <- enriched_data %>%
-    semi_join(df_season %>%
-                filter(.data$condition),
-              by = c("segment_id","season", "hour")
-              )
+  enriched_data <- enriched_data %>% semi_join(df_season %>% filter(condition), by = c("segment_id","season", "hour"))
 
   return(enriched_data)
 }
 
+#' @description
+#' A short description...
 #' Replace incomplete data with NA,
 #'
+#'
 #' @param enriched_data enriched data.frame containing all the data for all your sensors
 #' @param successive_day Integer. Number of day choosen. Default to 2
 #' @param uptime_choice Real. Uptime choosen. Default to 0.5
-#'
-#' @return enriched_data
+#' 
+#' @return enriched_data 
 #' @export
 #'
 #' @import dplyr
@@ -107,11 +110,12 @@ retrieve_missing_hours<-function(enriched_data,uptime_choice)
 #' replace_inactivity_period(traffic,
 #'                           uptime_choice=0.3,
 #'                           successive_day=1)
+
 replace_inactivity_period<-function (enriched_data,successive_day,uptime_choice)
 {
   list_clear_data <- list()
   seg_id<-unique(enriched_data$segment_id)
-
+  
   for(id in 1:length(seg_id))
   {
     df_segment<-enriched_data[enriched_data$segment_id==seg_id[id],]
@@ -120,25 +124,24 @@ replace_inactivity_period<-function (enriched_data,successive_day,uptime_choice)
       j=i
       while ((df_segment$car[i]==0 | df_segment$uptime[i]<uptime_choice) & i<length(df_segment$car))
       {i<-i+1}
-
+      
       diff_days<-abs(as.numeric(difftime(df_segment$day[i], df_segment$day[j], units = "days")))
-
+      
       if(diff_days>successive_day)
       {
         df_segment <- df_segment %>%
-          mutate_at(vars(.data$heavy_NA, .data$car_NA, .data$bike_NA, .data$pedestrian_NA),
-                    ~ ifelse(row_number() %in% j:i, NA,.))
+          mutate_at(vars(heavy_NA, car_NA, bike_NA,pedestrian_NA), ~ ifelse(row_number() %in% j:i, NA,.))
       }
     }
     list_clear_data[[id]]<-df_segment
   }
   enriched_data<-list_clear_data[[1]]
-
+  
   if(length(seg_id)>1)
   {
     for(i in 2:length(seg_id))
     {enriched_data<-rbind(enriched_data,list_clear_data[[i]])}
   }
-
+  
   return(enriched_data)
 }