Add three more features to sms
parent
364200a304
commit
6cf39ad9c4
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@ -28,8 +28,8 @@ READABLE_DATETIME:
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SMS:
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TYPES : [received, sent]
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METRICS:
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received: [count, distinctcontacts]
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sent: [count, distinctcontacts]
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received: [count, distinctcontacts, timefirstsms, timelastsms, countmostfrequentcontact]
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sent: [count, distinctcontacts, timefirstsms, timelastsms, countmostfrequentcontact]
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DAY_SEGMENTS: *day_segments
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# Communication call features config, TYPES and METRICS keys need to match
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@ -10,11 +10,25 @@ filter_by_day_segment <- function(data, day_segment) {
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}
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compute_sms_feature <- function(sms, metric, day_segment){
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sms <- sms %>% filter_by_day_segment(day_segment)
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feature <- switch(metric,
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"count" = sms %>% summarise(!!paste("com", "sms", sms_type, day_segment, metric, sep = "_") := n()),
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"distinctcontacts" = sms %>% summarise(!!paste("com", "sms", sms_type, day_segment, metric, sep = "_") := n_distinct(trace)))
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return(feature)
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if(metric == "countmostfrequentcontact"){
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# Get the most frequent contact
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sms <- sms %>% group_by(trace) %>%
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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(sms %>%
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filter_by_day_segment(day_segment) %>%
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summarise(!!paste("sms", sms_type, day_segment, metric, sep = "_") := n()))
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} else {
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sms <- sms %>% filter_by_day_segment(day_segment)
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feature <- switch(metric,
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"count" = sms %>% summarise(!!paste("sms", sms_type, day_segment, metric, sep = "_") := n()),
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"distinctcontacts" = sms %>% summarise(!!paste("sms", sms_type, day_segment, metric, sep = "_") := n_distinct(trace)),
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"timefirstsms" = sms %>% summarise(!!paste("sms", sms_type, day_segment, metric, sep = "_") := first(local_hour) + (first(local_minute)/60)),
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"timelastsms" = sms %>% summarise(!!paste("sms", sms_type, day_segment, metric, sep = "_") := last(local_hour) + (last(local_minute)/60)))
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return(feature)
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}
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}
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sms <- read.csv(snakemake@input[[1]])
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