37 lines
1.4 KiB
R
37 lines
1.4 KiB
R
library("tidyverse")
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library("glue")
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library("lubridate", warn.conflicts = F)
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options(scipen=999)
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assign_rows_to_segments <- function(data, segments){
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# This function is used by all segment types, we use data.tables because they are fast
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data <- data.table::as.data.table(data)
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data[, assigned_segments := ""]
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for(i in seq_len(nrow(segments))) {
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segment <- segments[i,]
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data[segment$segment_start_ts<= timestamp & segment$segment_end_ts >= timestamp,
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assigned_segments := stringi::stri_c(assigned_segments, segment$segment_id, sep = "|")]
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}
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data[,assigned_segments:=substring(assigned_segments, 2)]
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data
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}
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assign_to_time_segment <- function(sensor_data, time_segments, time_segments_type, include_past_periodic_segments, most_common_tz){
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if(nrow(sensor_data) == 0 || nrow(time_segments) == 0)
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return(sensor_data %>% mutate(assigned_segments = NA))
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if (time_segments_type == "FREQUENCY" || time_segments_type == "PERIODIC"){ #FREQUENCY segments are just syntactic sugar for PERIODIC
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source("src/data/datetime/assign_to_periodic_segments.R")
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sensor_data <- assign_to_periodic_segments(sensor_data, time_segments, include_past_periodic_segments)
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return(sensor_data)
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} else if ( time_segments_type == "EVENT"){
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source("src/data/datetime/assign_to_event_segments.R")
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sensor_data <- assign_to_event_segments(sensor_data, time_segments, most_common_tz)
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return(sensor_data)
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}
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} |