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title author date output
README.md
Mark Cherrie
18/09/2019
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uvR

The aim of the uvR package is to help researchers use and analyse UVR data in their studies. The package is in beta and currently only works with mac OS.

This work was supported by Health Data Research UK, an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and devolved administrations, and leading medical research charities. This work is part of HDR UK Scotland

Instructions for use

  • Create a new R project
  • Create a folder called 'boundary' with the geography that you want your UVR estimates by
  • Install the package
devtools::install_github("markocherrie/uvR")
  • Load the package
library(uvR)
  • Download two days of data
dates<-seq(as.Date("2019-07-10"), as.Date("2019-07-11"), by="days")
dates<-gsub("-", "", dates)
for(i in dates){
uvR::JAXA_download(i, "MYD", "uvb")
}
  • Convert that data to something usable
uvR::JAXA_convert()
  • Process the data for your area of interest (takes a while)
uvR::JAXA_process(61,43,-11,2)
  • Visualise the raster
rst<-raster(list.files("raster/", full.names = T)[1])
plot(rst)
  • Get summary statistics for your chosen geography
uvR::JAXA_extract("LA")
  • Visualise the output
multmerge = function(mypath){
  filenames=list.files(path=mypath, full.names=TRUE)
  datalist = lapply(filenames, function(x){read.csv(file=x,header=T)})
  Reduce(function(x,y) {merge(x,y)}, datalist)
}
# from: https://www.r-bloggers.com/merging-multiple-data-files-into-one-data-frame/

mergedf = multmerge("extract/")

mergedf<-reshape(mergedf, varying=c(3:4), direction="long", idvar="NAME", sep="", timevar="date")
mergedf$date<-as.Date(substr(mergedf$date, 8,15), format="%Y%m%d")

library(ggplot2)
## simple line chart in ggplot
p<-ggplot(data=mergedf, aes(x=date, y=MYD, group=NAME, color=NAME)) +
  geom_line() +
  geom_point() +
  labs(title="Mean daily UVB for Local Authorities in Scotland", x="Date" ,y="UVB (W/m2)") 
p