METgraphs_QCfile_looping.R

# script to loop through all CSV files in a folder,
# make line graphs (8 per page) of MET data 
# plus a second page with a wind rose
# from emailed CDMO QC files
# by Kim Cressman, Grand Bay NERR
# kimberly.cressman@dmr.ms.gov
# updated 2018-07-12

### IMPORTANT
# you need to have some packages installed
# only need to uncomment and run these once; you can ignore them in future script runs
# install.packages('clifro')
# install.packages('ggplot2')

### IMPORTANT 2
# Make sure the ONLY csv files in the folder you want to work in are QC files automatically emailed from the CDMO
# This script has NOT been error-proofed so if you have a file that it doesn't recognize, the script will stop in its tracks

### IMPORTANT 3
# The file-choice pop-up does NOT show up on top of other programs
# You MUST either click on the RStudio icon to minimize RStudio OR just minimize everything else to make the pop-up visible 

### INSTRUCTIONS
# 1 - Put your cursor somewhere in this window
# 2 - Push 'Ctrl' + 'A' to select the whole script
# 3 - Push 'Ctrl' + 'R' to run the script
# 4 - Minimize RStudio to get to the pop-up and choose the folder your QC files are in
# 5 - Magic happens
# 6 - Look in the folder you selected and pdf files should be there


# interactively choose which folder you want to work in
library(tcltk) #this package is part of base R and does not need to be installed separately
my.dir <- tk_choose.dir(getwd(), caption = "Choose which folder you want to work in")


# get the list of files in the directory that you want to graph
names.dir <- dir(path = my.dir, pattern = ".csv")
n <- length(names.dir)

for(i in 1:n)
{
  # find the next file in the loop
  myFile <- names.dir[i] 
  
  # make the full path to the file, first for reading, then for pdf output
  full_file_path <- paste0(my.dir, "/", myFile)
  
  
  # read in the file and generate names for output
  met.data <- read.csv(full_file_path)
  x <- nchar(myFile) # counting the characters in the file name
  Title = substr(myFile,1,x-4) # this should return the full name of the file (minus '.csv')
  Titlepdf <- paste0(my.dir, "/", Title, ".pdf") 

  
  #format DateTime as POSIXct, which will turn it into a number that can be graphed
  #we are retaining the format of mm/dd/yyyy hh:mm
  met.data$DateTime <- as.POSIXct(met.data$TIMESTAMP, format = "%m/%d/%Y %H:%M", tz = 'America/Regina')
  
  # open up a pdf file to print to
  pdf(file=Titlepdf) 
  
  # make the graph page layout 4 rows and 2 columns so all graphs will fit on a page
  par(mfcol=c(4,2), mar=c(2.1, 4.1, 1.1, 1.1), oma=c(1,1,2,1))
  
  
  #make line graphs
  
  # air temp
  plot(ATemp~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkred")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)

  # relative humidity  
  plot(RH~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkblue")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # baro pressure
  plot(BP~DateTime, data=met.data, 
       type="l", 
       xlab = "", 
       xaxt='n',
       col="darkgreen")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # wind speed
  plot(WSpd~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkslategray")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # max wind speed
  plot(MaxWSpd~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkorange")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # cumulative precip
  plot(CumPrcp~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkmagenta")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # PAR
  plot(TotPAR~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkturquoise")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # battery
  plot(AvgVolt~DateTime, data=met.data, 
       type="l", 
       xlab = "", xaxt='n',
       col="darkkhaki")
  axis.POSIXct(1, at=seq(min(met.data$DateTime, na.rm=TRUE), 
                         max(met.data$DateTime, na.rm=TRUE), length.out=5),
               format="%m/%d", cex.axis=0.9)
  
  # put the title of the file above all the plots on the page
  mtext(Title, outer=TRUE, side=3, cex=0.9, font=2)
  
  
  # make a wind rose on the next page
  
  #reset to one graph per page
  par(mfrow=c(1,1))
  
  library(clifro)
  library(ggplot2)
  
  p <- windrose(met.data$WSpd, met.data$Wdir, speed_cuts = c(2,4,6,8,10,15,30),
                legend_title='Wind Speed (m/s)', ggtheme='minimal') +     
      ggtitle(Title) +
      theme(plot.title = element_text(size = 12, face='bold'),
            legend.title = element_text(size=9),
            legend.text = element_text(size=8),
            legend.key.size = unit(5, 'mm'),
            axis.text.y = element_text(size=8),
            strip.text = element_text(face='bold')) 
  print(p)
  
  #turn off pdf printer
  dev.off()
}

print('Finished!')