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

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