rapids/src/features/location_barnett_metrics.R

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