41 lines
1.5 KiB
R
41 lines
1.5 KiB
R
source("packrat/init.R")
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library(dplyr)
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filter_by_day_segment <- function(data, day_segment) {
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if(day_segment %in% c("morning", "afternoon", "evening", "night"))
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data <- data %>% filter(local_day_segment == day_segment)
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return(data %>% group_by(local_date))
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}
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compute_wifi_feature <- function(data, feature, day_segment){
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if(feature %in% c("countscans", "uniquedevices")){
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data <- data %>% filter_by_day_segment(day_segment)
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data <- switch(feature,
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"countscans" = data %>% summarise(!!paste("wifi", day_segment, feature, sep = "_") := n()),
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"uniquedevices" = data %>% summarise(!!paste("wifi", day_segment, feature, sep = "_") := n_distinct(bssid)))
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return(data)
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} else if(feature == "countscansmostuniquedevice"){
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# Get the most scanned device
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data <- data %>% group_by(bssid) %>%
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mutate(N=n()) %>%
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ungroup() %>%
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filter(N == max(N))
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return(data %>%
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filter_by_day_segment(day_segment) %>%
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summarise(!!paste("wifi", day_segment, feature, sep = "_") := n()))
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}
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}
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data <- read.csv(snakemake@input[[1]], stringsAsFactors = FALSE)
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day_segment <- snakemake@params[["day_segment"]]
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requested_features <- snakemake@params[["features"]]
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features = data.frame(local_date = character(), stringsAsFactors = FALSE)
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for(requested_feature in requested_features){
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feature <- compute_wifi_feature(data, requested_feature, day_segment)
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features <- merge(features, feature, by="local_date", all = TRUE)
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}
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write.csv(features, snakemake@output[[1]], row.names = FALSE) |