64 lines
3.2 KiB
R
64 lines
3.2 KiB
R
source("packrat/init.R")
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library(dplyr)
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write_empty_file <- function(file_path, metrics_to_include){
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write.csv(data.frame(local_date= character(),
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hometime= numeric(),
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disttravelled= numeric(),
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rog= numeric(),
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maxdiam= numeric(),
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maxhomedist= numeric(),
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siglocsvisited= numeric(),
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avgflightlen= numeric(),
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stdflightlen= numeric(),
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avgflightdur= numeric(),
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stdflightdur= numeric(),
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probpause= numeric(),
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siglocentropy= numeric(),
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minsmissing= numeric(),
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circdnrtn= numeric(),
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wkenddayrtn= numeric()
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) %>% select(metrics_to_include), file_path, row.names = F)
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}
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# Load Ian Barnett's code. Taken from https://scholar.harvard.edu/ibarnett/software/gpsmobility
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file.sources = list.files(c("src/features/location_barnett"), pattern="*.R$", full.names=TRUE, ignore.case=TRUE)
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sapply(file.sources,source,.GlobalEnv)
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locations_to_use <- snakemake@params[["locations_to_use"]]
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accuracy_limit <- snakemake@params[["accuracy_limit"]]
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timezone <- snakemake@params[["timezone"]]
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metrics_to_include <- intersect(unlist(snakemake@params["metrics"], use.names = F),
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c("hometime","disttravelled","rog","maxdiam","maxhomedist","siglocsvisited","avgflightlen","stdflightlen","avgflightdur","stdflightdur","probpause","siglocentropy","minsmissing","circdnrtn","wkenddayrtn"))
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# By deafult we use all raw locations: fused without resampling and not fused (gps, network)
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location <- read.csv(snakemake@input[["raw"]], stringsAsFactors = F) %>%
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select(timestamp, latitude = double_latitude, longitude = double_longitude, altitude = double_altitude, accuracy)
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if(locations_to_use == "ALL_EXCEPT_FUSED"){
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location <- location %>% filter(provider != "fused")
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} else if (locations_to_use == "RESAMPLE_FUSED"){
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location <- read.csv(snakemake@input[["fused"]], stringsAsFactors = F) %>%
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select(timestamp, latitude = double_latitude, longitude = double_longitude, altitude = double_altitude, accuracy)
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} else if (locations_to_use != "ALL"){
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print("Unkown filter, provide one of the following three: ALL, ALL_EXCEPT_FUSED, or RESAMPLE_FUSED")
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quit(save = "no", status = 1, runLast = FALSE)
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}
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if (nrow(location) > 1){
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features <- MobilityFeatures(location, ACCURACY_LIM = accuracy_limit, tz = timezone)
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if(is.null(features)){
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write_empty_file(snakemake@output[[1]], metrics_to_include)
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} else{
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# Copy index (dates) as a column
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outmatrix <- cbind(rownames(features$featavg), features$featavg)
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outmatrix <- as.data.frame(outmatrix)
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outmatrix[-1] <- lapply(lapply(outmatrix[-1], as.character), as.numeric)
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colnames(outmatrix)=c("local_date",tolower(colnames(features$featavg)))
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write.csv(outmatrix %>% select(metrics_to_include), snakemake@output[[1]], row.names = F)
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}
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} else {
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write_empty_file(snakemake@output[[1]], metrics_to_include)
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} |