library("dplyr", warn.conflicts = F) compute_wifi_feature <- function(data, feature, time_segment){ if(feature %in% c("countscans", "uniquedevices")){ data <- data %>% filter_data_by_segment(time_segment) data <- data %>% group_by(local_segment) data <- switch(feature, "countscans" = data %>% summarise(!!feature := n()), "uniquedevices" = data %>% summarise(!!feature := n_distinct(bssid))) return(data) } else if(feature == "countscansmostuniquedevice"){ # Get the most scanned device mostuniquedevice <- data %>% filter(bssid != "") %>% group_by(bssid) %>% mutate(N=n()) %>% ungroup() %>% filter(N == max(N)) %>% head(1) %>% # if there are multiple device with the same amount of scans pick the first one only pull(bssid) data <- data %>% filter_data_by_segment(time_segment) print(data %>% filter(bssid == mostuniquedevice) %>% group_by(local_segment) %>% summarise(!!feature := n())) raise return(data %>% filter(bssid == mostuniquedevice) %>% group_by(local_segment) %>% summarise(!!feature := n()) ) } } rapids_features <- function(sensor_data_files, time_segment, provider){ wifi_data <- read.csv(sensor_data_files[["sensor_data"]], stringsAsFactors = FALSE) requested_features <- provider[["FEATURES"]] # Output dataframe features = data.frame(local_segment = character(), stringsAsFactors = FALSE) # The name of the features this function can compute base_features_names <- c("countscans", "uniquedevices", "countscansmostuniquedevice") # The subset of requested features this function can compute features_to_compute <- intersect(base_features_names, requested_features) for(feature_name in features_to_compute){ feature <- compute_wifi_feature(wifi_data, feature_name, time_segment) features <- merge(features, feature, by="local_segment", all = TRUE) } # features <- features %>% mutate_all(~replace(., is.na(.), 0)) return(features) }